Domain Decomposition Algorithms

OPTIMAL DECOMPOSITION OF FINITE ELEMENT MESHES VIA K-MEDIAN METHODOLOGY AND DIFFERENT METAHEURISTICS

In this paper the performance of four well-known metaheuristics consisting of Artificial Bee Colony (ABC), Biogeographic Based Optimization (BBO), Harmony Search (HS) and Teaching Learning Based Optimization (TLBO) are investigated on optimal domain decomposition for parallel computing. A clique graph is used for transforming the connectivity of a finite element model (FEM) into that of the cor...

Quasi-Primary Decomposition in Modules Over Proufer Domains

In this paper we investigate decompositions of submodules in modules over a Proufer domain into intersections of quasi-primary and classical quasi-primary submodules. In particular, existence and uniqueness of quasi-primary decompositions in modules over a Proufer domain of finite character are proved. Proufer domain; primary submodule; quasi-primary submodule; classical quasi-primary; decompo...

Updating finite element model using frequency domain decomposition method and bees algorithm

The following study deals with the updating the finite element model of structures using the operational modal analysis. The updating process uses an evolutionary optimization algorithm, namely bees algorithm which applies instinctive behavior of honeybees for finding food sources. To determine the uncertain updated parameters such as geometry and material properties of the structure, local and...

Biconjugate Decomposition Using ABS Algorithms

Optimization Based Nonoverlapping Domain Decomposition Algorithms and Their Convergence

We present some optimization based domain decomposition algorithms with nonoverlapping subdomains. A number of existing algorithms, as well as new algorithms, may be derived using this approach. Both continuous problems and their finite element discretizations are considered. Convergence properties are examined.

Evaluating Quasi-Monte Carlo (QMC) algorithms in blocks decomposition of de-trended

The length of equal minimal and maximal blocks has eected on logarithm-scale logarithm against sequential function on variance and bias of de-trended uctuation analysis, by using Quasi Monte Carlo(QMC) simulation and Cholesky decompositions, minimal block couple and maximal are founded which are minimum the summation of mean error square in Horest power.